Union Influence in Post-Socialist Europe

ILRReview, 65(3), July 2012. © by Cornell University.Print 0019-7939/Online 2162-271X/00/6501 $05.00

UNION INFLUENCE IN POST-SOCIALIST EUROPE

RICHARD CROUCHER AND MARIAN RIZOV*

Examining enterprise-level union influence in post-socialist coun-tries, the authors hypothesize that calculative human resource man-agement (HRM) is more strongly associated with low levels of union influence than collaborative HRM. Using the United Kingdom as a benchmark, they find that in the countries under study, calculative HRM is indeed more damaging to union influence than collabora-tive, although to a much lesser extent than in the United Kingdom. They also find that union influence corresponds to enterprise union density and is most apparent when the business cycle is unfavorable; they explain their findings by reference to East European members’ continued attachment to unionism for nonbargaining reasons.

We examine enterprise-level union influence in post-socialist countries (PSCs), and seek to discover its antecedents. Research on union influ-

ence at the enterprise level in post-socialist Europe is sparse, despite the fact that unions retain highly decentralized structures and funds. Yet influential unions are more likely to provide a solid basis for the European Union (EU) social dialogue processes; conversely, unions at this level that are not influ-ential may eventually erode the European model. We find that union den-sity, collaborative HRM, and the business cycle are all significant antecedents of union influence and that previous national-level estimates are a useful but imprecise guide to enterprise-level influence.

Management and Unions before 1989

Many researchers suggest (Vos 2006; Knell and Srholec 2007; Meardi 2007a, 2007b; Woolfson 2007; Trif 2008) that soviet management legacies remain influential in PSCs. Labor management, like unions, had a major political role within the socialist system (Tung and Havlovic 1996), and this empha-sized the need to build socialism through efficient production (Kornai 1992). Unions were part of enterprise management. Little importance was accorded to the personnel function, which consisted of selection, discipline and, to some extent, training (Tung and Havlivich 1996). Although the per-sonnel function is now widely referred to as HRM, it often has no strategic

*Richard Croucher is Professor of Comparative Employment Relations and Director of Research at Middlesex University Business School. Marian Rizov is Reader in Economics at Middlesex University Business School.

Cranet data are the property of the Cranet network, coordinated by Cranfield School of Management, Cranfield University in the UK. Data are administered by the network coordinator located there.

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role. In many PSCs much of this management system remains (Brewster, Mayrhofer, and Morley 2005).

Trade unionism is still marked by the communist experience (Soulsby and Clark 2007; Noelke and Vliegenthart 2009); union roles may in some countries still be filled by managers (Trif 2008). Pre-1989 union functions were essentially corporatist: to integrate and motivate workers. Unions also had major political roles as transmission belts for Communist policy, which currently creates legitimacy problems (Meardi 2006). Although they ac-quired minor representational functions under communism (Kornai 1992), they also had large legal departments which remain important in many unions (Trif 2005; Meardi 2006). Membership was compulsory, and unions stood largely aloof from workers’ informal bargaining over piece rates (Haraszti 1978). They had important welfare functions and allocated re-sources to providing workers with holidays for themselves and their families, housing, and money when they had particular needs. Workers were encour-aged to identify with the labor collective, an ideological construct acquiring concrete reality through collective workplace events and the union itself. Current union membership can reflect continuing identification with these functions even though union resources in the welfare area are much dimin-ished and no longer include housing (Trif 2005). The social movement unionism that emerged in some countries before 1989 was superimposed on this situation.

Trade Unions since 1989

Before 1989 union influence was simply exercised, if at all, as part of the management function. When a market system began to be implemented, this disappeared: management was then influenced by their perceptions of unions’ capacity to mobilize their members. We term this direct union influ-ence. Unions, however, might also retain some influence through their ca-pacity to shape members’ views and hence their levels of commitment to management initiatives. Their legal watchdog role may also allow pressure to be put on management. We call these forms indirect influence because they are less reliant on mobilization capacity. The basis for this is in mem-bers’ perceptions of union functions. Indirect influence is likely to be stron-ger in the PSCs than elsewhere, where union bargaining functions are more central. In short, union influence may have either direct or indirect influ-ence; and management may use the latter to shape a form of unionism that presents little challenge to management prerogative.

PSCs have been strongly exposed to global markets and financial institu-tions, bringing mass privatization, unemployment, and a shift away from full-time permanent employment (Bohle and Greskovits 2007; Baranowska and Gebel 2008; Psychogios, Szamosi, and Wood 2010; Williams 2010). Workers are therefore invariably in weak positions, except where skill short-ages exist, and this weakness is reflected in unions’ low mobilization capac-ity (Psychogios et al. 2010). Their direct influence is therefore weak.

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Initially, in 1989 and 1990, unions were seen as a possible focus for social unrest, likely to defend privileges accorded the working class under commu-nism. In that brief period, they were brought into tripartite discussion (Ca-sale 1999). Yet governments gradually set tripartism aside, giving way to a long period of neoliberal-inspired legislation and employer hostility. The international financial institutions insisted on labor market reform and ex-plicitly linked it to a need to reduce union influence (Giacobbe-Miller, Miller, and Victorov 1998).1 By the mid-2000s, discussion centered on unions’ incapacity to act as credible social partners within the EU (Meardi 2006).

PSCs show considerable diversity, but they share common features that corrode union membership and influence. EU legislation and influence have had liberalizing effects (Woolfson 2007; Meardi 2007b), although some suggest that EU influence simply reproduces prior levels of joint regu-lation (Trif 2008). Wage bargaining is often decentralized and in some countries may be conducted by employee representatives instead of unions; works councils, where they exist, have only weak consultation powers, and industrial action is rare (ILO 2000; Funk and Lesch 2004). In the one coun-try with a relatively strong union movement, Slovenia, tripartism has oper-ated successfully since the mid-1990s (Frail 2009). Elsewhere, experts judge unions to be much weaker (Mailand and Due 2004; to compare this judg-ment with the ILO view, see Dimitrova and Vilrokx 2005). National-level tripartism is much less effective than in Western Europe because it was insti-tuted through a top-down process (Mailand and Due 2004). Ost (2000) de-scribes it as “illusory corporatism”: driven by new elites, it serves their liberalizing purposes. While these arrangements give formal voice to unions, Ost argues that labor is complicit in a process that diminishes its own influ-ence. Outside sectors protected from competition, many unions are too weak to insist on observance of any agreement, much less to bargain supple-ments to national agreements as legally permitted in Romania (Trif 2005; EFILWC 2009). Enterprise agreements on occasion specify worse terms and conditions than legal minima (Bernaciak, Duman, and Scepanovic 2010).

Most national union density estimates fall between 16% and 22% (for Bulgaria, Czech Republic, Estonia, Hungary, Slovakia, and Slovenia) and, at either extreme, Slovenia at 44% and Estonia at 7.6% (EIRO 2010). Slove-nian strength and Baltic weakness are reflected in other findings in terms of union wider capacities (Buchen 2007; Stockhammer and Onaran 2009), their ability to conduct social dialogue (Mailand and Due 2004), to carry out extrajudicial action (Welz and Kauppinen 2005), and to defend women members (Pollert 2005).

1In several studies the elimination of labor hoarding is identified as an important (necessary) compo-nent of enterprise restructuring policies promoted by international financial institutions. Another im-portant (sufficient) component is new investment in productive assets rather than using funds for enterprise survival. The success of restructuring policies is conditional on eliminating soft budget con-straints (Konings, Rizov, and Vandenbussche 2003, Rizov 2005), directly linked to abandoning the state’s role in ensuring full employment.

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After 1990 unions made efforts to become more mobilizing and bargain-ing bodies (Gennard 2007; Croucher and Cotton 2009). Yet extensive quali-tative functional change has proved difficult, and because of mixed verdicts from experts, it remains unclear how far their efforts have succeeded. Thirkell, Petkov, and Vickerstaff (1998) cited MSzOSz in Hungary and CITUB in Bulgaria as reformed federations that were stronger than they had been before 1999 previously. Gennard (2007), analyzing print unions’ positions, passed a more qualified judgment. Crowley (2004) went further, arguing that many unions remained unreformed, which helped to explain labor quiescence, while King (2007) characterizes Central European unions as highly ineffective.

Unions at the enterprise level may have certain limited resources to but-tress their influence. First, high union density may provide representative legitimacy and underpin some prospect of direct influence (Vernon 2006). Second, management can concede union influence to help them effect change (Crowley 2004; Croucher 2010). This may be buttressed by the legal watchdog role, union welfare functions and continued identification with it as an institutional embodiment of the “labor collective.” The legal watchdog role acquires particular significance where relatively strong worker protec-tion remains in place, as in some countries (Trif 2005). Finally, they may exercise indirect influence on management by diffusing discontent on the shop floor (Gomez-Mejia and Welbourne 1994).

Forms of HRM

HRM is used by Western companies, to some extent by private companies, and even occasionally in the state sector (Brewster et al. 2005). Forms of HRM all emphasize alignment of employer and employee interests, but vary considerably. Gooderham, Nordhaug, and Ringdal (1999, 2006) identified two forms that broadly reflect, on the one hand, American and, on the other, West European approaches: calculative and collaborative HRM. Calcula-tive HRM treats labor as an abstract factor of production, stressing individu-alized reward, appraisal, and employee development monitoring systems. Collaborative approaches have a more humanistic orientation, viewing em-ployees as active partners, and emphasizing intensive downward communi-cation with employees at all levels (Gooderham et al. 1999). Collaborative approaches are part of relational policies (Gospel and Pendleton 2005) and, as Gooderham et al. 1999 acknowledge, have much in common with soft HRM (Storey 2001). The Gooderham et al. typology does not reflect a full set of soft HRM practices; the soft characterization explicitly includes a relatively positive attitude to unionization.

We adopt this conceptualization because it captures two paradigmatic sets of practices. We prefer the Gooderham et al. conceptualization to the vaguer, normative or prescriptive hard and soft HRM dichotomy (see, for example, Storey 2001). Also unlike the hard and soft conceptualization, the

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Gooderham et al. typology has the advantage that it treats unions as exoge-nous, and there is therefore no problem of endogeneity in measurement.

Calculative HRM is the form usually adopted by private companies in the PSCs. It allows and reflects, as the concept’s authors explain, higher levels of management choice. Gooderham et al. (1999) argue that calculative HRM is strongly linked to managements’ wish to increase their autonomy and scope for initiative. Individualized pay systems have been adopted and pro-moted to other companies by multinational corporations (MNCs). MNCs operate in the PSCs (EFILWC 2009). Gooderham et al. (1999) suggest that calculative HRM is closely associated with reduced union influence in West-ern Europe; unions resist it, but they don’t resist the collaborative form. This is because it is based on a negative view of collective representation and emphasizes individual assessment and reward. This may also have an effect in the PSCs, both by concrete results, such as reducing the material signifi-cance of collective bargaining, and also in a less direct way by sending the message to employees that collective institutions are unwelcome.

In the PSCs, however, both union functions and members’ perceptions of what these should be are fundamentally different from those in much of the rest of the world. In other societies, and especially in the liberal market economies, we would not expect welfare and affective considerations to have similar relevance. In our analysis, therefore, we include the United Kingdom as a benchmark, since we expect calculative HRM to have a marked negative effect on union influence there, as Gooderham et al.’s the-ory predicts.

We therefore propose this hypothesis: In PSCs, calculative HRM is associ-ated with lower union influence than the collaborative form, but less so than in the United Kingdom benchmark.

Data and Variables

Our data derive from the 2003−4 round of Cranet, an international enter-prise-level survey of HRM practices conducted at regular intervals since 1989 across a large number of countries by a well-established international research network. Cranet is by far the most comprehensive international survey of HR policies and practices at the organizational level. The survey encompasses all areas of economic activity, but it excludes firms employing fewer than 100 staff and targets organizations employing more than 200. Respondent firms are chosen to reflect the broad industrial composition by employment within each country surveyed. It covers private and public organizations in 22 European countries, as well as some dozen others (Brewster et al. 2005). It is directed at HR managers or, in the absence of an HR manager, the senior manager responsible for HR issues, and it uses predominantly closed questions on policies and practices rather than atti-tudes. This ensures unambiguous responses on actual policies and practices. The questions are agreed on by members of the network, translated into the appropriate language, and then translated back into English to identify any

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problems with international meaning and comparability. In the countries involved in our sample, the survey was administered by mail. Data collection in these countries poses considerable and specific difficulties (Drzewiecka 2007). There is a tradition of secrecy among managers (Danilovich and Croucher 2011), which can be partially overcome by using local researchers in each country. Full technical details are available in Brewster et al. (2005).

We use data from all the PSCs for which data are available (Bulgaria, Czech Republic, Estonia, Hungary, Slovakia, and Slovenia) and, as our lib-eral market economy benchmark, from the United Kingdom. These coun-tries exhibit diverse institutional settings, and they include a Balkan country (Bulgaria) as well as a Baltic one (Estonia) and a group of significant Cen-tral European economies. All are members of the EU. We also include in our sample firms that are part of multinational companies (MNCs). The incidence of MNCs in our sample exhibits a pattern consistent with aggre-gate statistics on MNCs’ presence in the region (WIIW 2003).

Our main dependent variable is union influence at the firm level (TUIN), measured as a dichotomous variable with a value of 1 when managers re-ported some union influence and 0 otherwise. We asked managers if union influence has increased, decreased, or remained the same over the previous three years, or if no union influence existed. We classify the first three cate-gories as “some influence” and the last as “no influence.” We believe that treating the question in this way provided reliable information; we experi-mentally redefined the variable by excluding the decreased category, but the results, available on request, remained qualitatively the same. Using these data, it is impossible to distinguish between direct and indirect influ-ence, as we do on the theoretical level. We also analyze unions’ presence (TUPR) in firms and measure this on a scale with six categories according to the share of firm employees in union membership.2 Verma, Kochan, and Wood (2002) argue that union density is the best overall indicator of union influence. Thus, by using both TUIN and TUPR, we believe that we achieve the most reliable indication of whether union influence exists. Table 1 dem-onstrates the high correlations (Pearson correlation coefficients) of TUIN and TUPR both by country and for the total PSCs and United Kingdom samples.

In extended regressions, we use two measures of the two major types of labor management practices as formulated by Gooderham et al. (1998, 1999), calculative HRM (CALC) and collaborative HRM (COLL) as control variables. We augment the collaborative HRM measure with group practice components following Rizov and Croucher (2009). The calculative HRM measure is also augmented by our use of a compulsory redundancy compo-nent. We note that in this analysis we use CALC and COLL to control for the impact of HRM practices on union influence, rather than study the prac-tices themselves in depth. Composite scales are used for CALC and COLL,

2The six categories are defined as follows: category 0 corresponds to 0% share, 1 to 1%10% share, 2 to 11%–25% share, 3 to 26%–50% share, 4 to 51%–75% share, and 5 to 76%–100% share.

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comprising indicators of HRM practices of 15 and 13 components, respec-tively. In identifying the components of each scale we pay attention to the contexts of both the PSCs and the United Kingdom.

The CALC scale is a composite of indicators for base and variable pay that are directly related to performance for all employee categories, regular for-mal appraisal for managers, professionals, clerical, and manual workers, use of formal appraisal in informing career and pay decisions as well as use of compulsory redundancies. We were unable to reproduce all of the original Gooderham et al. calculative scale because the two items on monitoring training effectiveness were not used in the 2004 questionnaire; however, it seems likely that the use of the appraisals questions may to some extent mitigate this issue.

The COLL scale comprises indicators for formal strategy briefings of all categories of employees and the presence of a written mission and corpo-rate values statement, extended by measures for minority inclusion, career development through team work, the presence of mechanisms for two-way communication at team level, and the existence of a works council or joint consultative committee.

Each HRM indicator is an ordinal categorical variable. We apply Mok-ken’s nonparametric scaling model (Mokken and Lewis 1982) to compute our synthetic HRM indices as did Gooderham et al. (1999). The unweighted sum of item scores must be monotonously related to the latent true scores, as demonstrated by Sjitsma, Debets, and Molenaar (1990). This implies that Mokken’s model provides only estimates of the scale scores at ordinal level. The primary scaling criterion is Loevinger’s H-coefficient of homogeneity. A set of items constitutes a scale if the aggregate has an H-value exceeding 0.30; values above 0.50 indicate strong scales. The consistency of the scales is also verified by Cronbach’s Alpha, which increases as the intercorrelations among scale items increase and is thus an internal consistency estimate of the scale’s reliability. Because intercorrelations among test items are maximized, when all items measure the same construct, Cronbach’s Alpha is taken as in-directly indicating the degree to which a set of items measures a single uni-dimensional latent construct. Alpha values above 0.70 indicate a strong scale. Details of the items included in the scales, results of the scaling, and our reliability analysis are reported in the Appendix, Tables A.1a and A.1b for the PSC and U.K. samples, respectively.

In Table 2 we report for all PSCs in our sample by country summary statis-tics on union influence, MNC presence (measured as a share of surveyed

Table 1. Correlation of Union Influence (TUIN) and Presence (TUPR) in the PSCs and the United Kingdom

Bulgaria Hungary Estonia Slovenia SlovakiaCzech

RepublicTotal PSCs U.K.

Correlation coefficient 0.64 0.85 0.66 0.68 0.80 0.70 0.76 0.70

Note: All (Pearson) correlation coefficients are significant at the p = 0.001 level.

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firms), the importance of private ownership, and the prevalence of calcula-tive and collaborative HRM practices. The summary statistics confirm that our data approximate to the empirical facts established by other studies using different data sources.

Following the conceptual frameworks of Gooderham et al. (1998, 1999) and of Rizov and Croucher (2009), we control in our regression analysis for firm characteristics affecting union influence and the prevalence of HRM practices. These are log of firm size (Firm size), log of firm age (Firm age), and a dummy variable indicating private ownership (Private firm). In all re-gressions a control dummy variable for foreign ownership and management in large organizations is also included (Multinational firm). Market condi-tions are controlled for by a three-step ordinal scale indicating whether the firm’s market is declining, steady, or growing (Business cycle). Industrial sec-tor information, a set of industry dummy variables (Primary industries, Manu-facturing, and Construction), is included in extended regression specifications (Services is the reference category). Finally, we capture cross-country differ-ences with country dummy variables used in extended regression specifica-tions to control for variations in institutional settings. Summary statistics and short definitions of all regression variables are reported in Table 3. Cor-relation matrices for selected regression variables are presented in the on-line version of the paper (Tables A.2a and A.2b for PSCs and U.K. samples, respectively) on http://eprints.mdx.ac.uk/8038/. The low correlations be-tween regression variables indicate no endogeneity problems.

Econometric Analysis

Determinants of Union Influence

Given that the dependent variable of main interest (union influence) is di-chotomous we first estimate relationships by a probit regression and report the estimation results (marginal effects) in Table 4a for the PSCs and in Table 4b for the United Kingdom. Following Gooderham et al. (1999) and Rizov and Croucher (2009), we start with a base specification in which the explanatory variables are simply the main firm characteristics. In a second extended specification we add information on private and foreign owner-

Table 2. Union Influence, Ownership, and HRM Practices in the PSCs

TUIN MNC PRIV CALC COLL

Bulgaria 0.58 (0.49) 0.17 (0.38) 0.64 (0.48) 0.56 (0.30) 0.47 (0.31)Czech Republic 0.82 (0.39) 0.22 (0.42) 0.86 (0.35) 0.74 (0.26) 0.78 (0.25)Estonia 0.38 (0.49) 0.15 (0.35) 0.62 (0.49) 0.44 (0.29) 0.68 (0.27)Hungary 0.60 (0.49) 0.27 (0.44) 0.62 (0.49) 0.50 (0.30) 0.61 (0.32)Slovakia 0.55 (0.50) 0.20 (0.40) 0.82 (0.39) 0.56 (0.29) 0.58 (0.29)Slovenia 0.91 (0.29) 0.12 (0.30) 0.63 (0.48) 0.70 (0.27) 0.67 (0.27)

Notes: Means and standard deviations (in parentheses) are reported. CALC and COLL indices are normalized to the interval [0, 1]. Abbreviations: TUIN, union influence; MNC, multina-tional firm; PRIV, private firm; CALC, calculative HRM; COLL, collaborative HRM.

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ship. Next, the specification (in Table 4a) also includes a set of PSCs dummy variables that capture variations in institutional specificities across countries, with reference to the Czech Republic. We further extend the specification with a measure of market conditions and subsequently add a set of industry dummy variables with aggregate services as the reference category. The sta-bility of coefficients in all regressions when introducing stepwise explanatory variables indicates no endogeneity problems.3 Nevertheless, we are cautious in drawing conclusions regarding causality and interpret our results simply

3In all regressions we have included variables describing key respondent characteristics to control for a possible measurement error due to self-reporting. The individual-level control variables are gender, education, and years of service in the organization, and we assume that they are not correlated with the

Table 3. Summary Statistics

Variable Definition PSCs U.K.

TUIN Union influence dummy variable equal to 1 and 0 otherwise 0.63 (0.37)

0.64 (0.48)

TUPR Union presence scale ranging between 0 and 5 (low-high) 2.13 (1.26)

1.90 (1.67)

CALC Calculative HRM composite scale ranging between 0 and 15 8.86 (2.92)

7.94 (3.27)

COLL Collaborative HRM composite scale ranging between 0 and 13 7.21 (2.95)

8.38 (2.63)

Firm size Log of firm size (total labor force) 5.78 (1.23)

6.46 (1.28)

Firm age Log of firm age (years) 2.83 (1.03)

3.54 (1.13)

Multinational firm (MNC)

Dummy variable which is 1 if the firm is a foreign multinational and 0 otherwise

0.16 (0.37)

0.14 (0.35)

Private firm Dummy variable which is 1 if the firm is private and 0 otherwise 0.70 (0.46)

0.70 (0.46)

Business cycle Scale of business cycle conditions ranging between 1 and 3 (recession-expansion)

2.38 (0.68)

2.28 (0.75)

Primary industries Dummy variable which is 1 for primary industries and 0 other-wise

0.10 (0.30)

0.03 (0.18)

Manufacturing Dummy variable which is 1 for manufacturing and 0 otherwise 0.23 (0.42)

0.31 (0.46)

Construction Dummy variable which is 1 for construction and 0 otherwise 0.04 (0.19)

0.03 (0.18)

Services Dummy variable which is 1 for services retail and wholesales and 0 otherwise

0.63 (0.84)

0.51 (0.50)

Bulgaria Dummy variable which is 1 if the firm is in Bulgaria and 0 oth-erwise

0.18 (0.38)

Czech Republic Dummy variable which is 1 if the firm is in Czech Republic and 0 otherwise

0.08 (0.28)

Hungary Dummy variable which is 1 if the firm is in Hungary and 0 oth-erwise

0.11 (0.32)

Estonia Dummy variable which is 1 if the firm is in Estonia and 0 other-wise

0.14 (0.34)

Slovakia Dummy variable which is 1 if the firm is in Slovakia and 0 oth-erwise

0.30 (0.46)

Slovenia Dummy variable which is 1 if the firm is in Slovenia and 0 oth-erwise

0.19 (0.39)

Note: Means and standard deviations (in parentheses) are reported. Number of observations used in calculating summary statistics is 747 for PSC sample and 800 for the United Kingdom.

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as evidence of correlations between variables. We conceptualize the results as showing a mutually determined relationship; since management clearly has control, its policies are of great significance, but union policies and prac-tices are also likely to have some impact on the relationships.

Comparing overall results for the United Kingdom and the PSCs, the ef-fects’ signs are the same, except for the Multinational firm variable; however, for some variables the level of significance is higher and the coefficients’ magnitudes appear larger for the PSCs sample.4 For the PSC sample, firm size and age have positive and statistically significant impacts on union influ-

firm-level variables. Individual-level controls were neither individually nor jointly statistically significant in any regression, and therefore their coefficients were not reported.

4We test for differences in coefficients for the PSC and U.K. samples using Wald tests and find that jointly for all coefficients the differences are significant at 10% level or better for the majority of the models.

Table 4a. Determinants of Union Influence (TUIN) in the PSCs (probit estimator)

Variables

Models

(1) (2) (3) (4) (5) (6)

Firm size 0.165*** (0.018)

0.175*** (0.018)

0.166***(0.020)

0.170*** (0.020)

0.153*** (0.020)

0.149*** (0.021)

Firm age 0.094*** (0.019)

0.077 *** (0.020)

0.062 ***(0.021)

0.056 *** (0.021)

0.056 *** (0.021)

0.055*** (0.021)

Multinational firm –0.166*** (0.054)

–0.155***(0.056)

–0.145*** (0.056)

–0.161*** (0.057)

–0.164*** (0.058)

Private firm –0.152*** (0.042)

–0.179*** (0.042)

–0.162*** (0.043)

–0.170*** (0.046)

–0.164*** (0.046)

Bulgaria –0.331*** (0.086)

–0.320*** (0.087)

–0.330*** (0.089)

–0.310*** (0.092)

Hungary –0.201** (0.097)

–0.194** (0.097)

–0.195** (0.099)

–0.196** (0.099)

Estonia –0.379*** (0.088)

–0.374*** (0.088)

–0.369*** (0.090)

–0.399*** (0.089)

Slovenia 0.153* (0.077)

0.158* (0.077)

0.160* (0.078)

0.143* (0.079)

Slovakia –0.093 (0.082)

–0.086 (0.082)

–0.094 (0.083)

–0.085 (0.083)

Business cycle –0.088*** (0.030)

–0.070** (0.030)

–0.074** (0.031)

Primary industries 0.185*** (0.052)

0.176*** (0.053)

Manufacturing 0.113*** (0.044)

0.112*** (0.044)

Construction 0.088 (0.082)

0.080 (0.083)

COLL 0.103** (0.050)

CALC –0.116* (0.067)

Pseudo R_squared 0.21 0.28 0.40 0.41 0.46 0.49Number observations 747 747 747 747 747 747

Notes: Coefficients reported represent marginal effects. Reference country is Czech Republic, and refer-ence industry is Services. Level of significance of estimated coefficients is indicated as follows: 1%***, 5%**, 10%*. COLL and CALC HRM scales are in logs.

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ence. Union influence, however, is significantly statistically weaker in for-eign-owned and private firms. Using the Czech Republic as the reference country, firms in Bulgaria, Hungary and Estonia are characterized by weaker union influence. In Slovenia, union influence is, as expected, stronger while influence in Slovakia is similar to that in the Czech Republic. All the results are consistent with other researchers’ national findings and remain robust when we control for business cycle and market conditions.

Significantly, the business cycle is negatively correlated with union influ-ence in PSCs: In periods of favorable market conditions influence is low but increases when the business cycle moves unfavorably. Adding a set of industry controls reproduces the results from previous specifications and also sug-gests important differences across industries. Given aggregate services as a reference category, union influence is stronger in primary industries and manufacturing, while in the construction sector it is similar to services.

Finally, we extend the last specification, considering the association of HRM with union influence and report our results in Table 4a, column 6, and Table 4b, column 5, for the PSCs and the U.K. samples, respectively. Interestingly, the two HRM scales’ coefficients exhibit the same pattern but differ in magnitudes for the two samples as verified by Wald tests, which are significant at 5% level. For the PSC sample the coefficients of COLL and CALC are smaller in magnitude, confirming the expectations we have dis-

Table 4b. Determinants of Union Influence (TUIN) in the United Kingdom (probit estimator)

Variables

Models

(1) (2) (3) (4) (5)

Firm size 0.120*** (0.015)

0.117*** (0.016)

0.118*** (0.016)

0.118*** (0.016)

0.116***(0.016)

Firm age 0.033** (0.016)

0.031** (0.016)

0.031** (0.016)

0.026 (0.016)

0.020 (0.017)

Multinational firm 0.063 (0.046)

0.059 (0.047)

0.043 (0.048)

0.055 (0.047)

Private firm –0.275*** (0.034)

–0.285*** (0.034)

–0.346*** (0.033)

–0.285**(0.038)

Business cycle –0.033 (0.023)

–0.026 (0.024)

–0.024 (0.024)

Primary industries 0.202***(0.064)

0.199***(0.060)

Manufacturing 0.243*** (0.036)

0.228***(0.036)

Construction 0.082 (0.087)

0.082 (0.082)

COLL 0.243***(0.050)

CALC –0.306***(0.054)

Pseudo R_squared 0.15 0.21 0.21 0.26 0.32Number observations 800 800 800 800 800

Notes: Coefficients reported represent marginal effects. Reference industry is Services. Level of significance of estimated coefficients is indicated as follows: 1%***, 5%**, 10%*. COLL and CALC HRM scales are in logs.

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UNION INFLUENCE IN POST-SOCIALIST EUROPE 641

cussed about the processes and their probable effects on union influence. For the U.K. sample, the pattern is as expected: The coefficient of COLL is positive while the coefficient of CALC is negative; both are highly statistically significant.

Extensions and Robustness Analysis

We need to consider the possibility that union influence and HRM practices, as measured by the CALC and COLL scales, are simultaneously determined. We conceive of union influence as arising from interactive, negotiated pro-cesses between management and unions. To test and control for simultane-ity we specify a system of three equations and estimate it by SURE (seemingly unrelated regression). SURE uses the asymptotically efficient, feasible, GLS algorithm (described in Greene 2003: 340–362) and jointly estimates the three regressions, each with its own error term, as errors are allowed to be correlated. Stepwise expansion of the equation specifications follows the same pattern as in Tables 4a and 4b. Estimation results for the union influ-ence equation are reported in Tables 5a and 5b for the PSCs and the U.K.

Table 5a. Determinants of Union Influence in the PSCs (SUR estimator)

Variables

Models

(1) (2) (3) (4) (5)

Firm size 0.136*** (0.013)

0.138*** (0.013)

0.126*** (0.013)

0.128*** (0.013)

0.114*** (0.014)

Firm age 0.080*** (0.016)

0.067*** (0.016)

0.049*** (0.016)

0.045*** (0.016)

0.044*** (0.016)

Multinational firm –0.140*** (0.044)

–0.125*** (0.042)

–0.116*** (0.042)

–0.131** (0.042)

Private firm –0.123*** (0.037)

–0.138*** (0.036)

–0.124*** (0.036)

–0.137*** (0.039)

Bulgaria –0.260*** (0.065)

–0.248*** (0.064)

–0.245*** (0.064)

Hungary –0.151** (0.068)

–0.146** (0.068)

–0.136** (0.067)

Estonia –0.313*** (0.068)

–0.307*** (0.068)

–0.290*** (0.067)

Slovenia 0.096 (0.062)

0.095 (0.062)

0.100* (0.061)

Slovakia -0.088 (0.060)

-0.083 (0.059)

-0.086 (0.059)

Business cycle -0.067 *** (0.022)

-0.059 *** (0.023)

Primary industries 0.162 *** (0.049)

Manufacturing 0.107 *** (0.036)

Construction 0.060 (0.064)

R_squared 0.23 0.30 0.46 0.47 0.51Number observations 747 747 747 747 747

Notes: Coefficients reported represent marginal effects. Reference country is Czech Republic, and reference industry is Services. Level of significance of estimated coefficients is indicated as follows: 15%***, 5%**, 10%*.

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642 ILRREVIEW

samples, respectively, while the (auxiliary) results for the HRM practices’ equations are reported in the online version of the paper (Tables A.3a, A.3b, A.4a, and A.4b) on http://eprints.mdx.ac.uk/8038/. Comparing re-sults for the determinants of union influence in the United Kingdom and in the PSCs, the signs of the effects are the same, except for the Multinational firm variable. The main conclusion we draw from Tables 5a and 5b is that the coefficients appear very similar to those reported in Tables 4a and 4b, respectively. The fact that the coefficient signs are the same and the magni-tudes are very similar suggests that our results are robust. Further, a Breusch-Pagan test (Breusch and Pagan 1980) of independence (no correlation of residuals) rejects the hypothesis of zero correlation of the residuals and im-plies that union influence and HRM practices indeed are correlated and likely to be simultaneously determined.5

As a further robustness check we estimate SURE regressions with a mea-sure of union presence (TUPR) rather than influence for both samples. Al-though our main variable of interest is union influence, we consider union presence a necessary condition and the best proxy for influence (Verma et al. 2002; Vernon 2006). Therefore, estimating regressions with TUPR can reveal if there is a gap between (necessary) conditions and realization. The results are reported in Tables 6a and 6b and appear qualitatively similar to the results for union influence reported in Tables 5a and 5b. The depen-

5The Breusch-Pagan Chi-square statistic, a Lagrange Multiplier statistic, rejects the null hypothesis of no correlation in all regressions and is significant at 1% level or better.

Table 5b. Determinants of Union Influence in the United Kingdom (SUR estimator)

Variables

Models

(1) (2) (3) (4)

Firm size 0.102*** (0.013)

0.088*** (0.012)

0.088*** (0.012)

0.103*** (0.012)

Firm age 0.033** (0.014)

0.030** (0.014)

0.030** (0.014)

0.024* (0.014)

Multinational firm 0.067 (0.046)

0.063 (0.046)

0.053 (0.045)

Private firm –0.270*** (0.038)

–0.282*** (0.039)

–0.296*** (0.040)

Business cycle –0.031 (0.022)

–0.024 (0.022)

Primary industries 0.225*** (0.084)

Manufacturing 0.252*** (0.038)

Construction 0.074 (0.085)

R_squared 0.22 0.28 0.28 0.38Number observations 800 800 800 800

Notes: Coefficients reported represent marginal effects. Reference industry is Services. Level of significance of estimated coefficients is: 1%***, 5%**, 10%*.

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UNION INFLUENCE IN POST-SOCIALIST EUROPE 643

dent variable, TUPR, is a scale with six categories rather than a dichotomous one, meaning that the coefficients are not directly comparable in terms of magnitudes.6 The signs of the estimated coefficients are the same, while the coefficient magnitudes appear proportionately similar. This qualitative simi-larity indicates that the degree of unions’ presence likely approximates their influence.

Discussion and Conclusions

Our main contribution has been to show the antecedents of union influ-ence at enterprise level in the PSCs. Although both forms of HRM have the expected associations with union influence, these are more muted than in the United Kingdom. Union influence is also associated with high union

6The results for the HRM practices equations are reported in the online version of this article (Tables A5a, A5b, A6a, and A6b) on http://eprints.mdx.ac.uk/8038/ and are quite similar to the SURE results with union influence.

Table 6a. Determinants of Union Presence in the PSCs (SUR estimator)

Variables

Models

(1) (2) (3) (4) (5)

Firm size 0.479*** (0.052)

0.489*** (0.051)

0.468*** (0.050)

0.418*** (0.050)

0.393*** (0.050)

Firm age 0.465*** (0.063)

0.415*** (0.063)

0.312*** (0.059)

0.296*** (0.059)

0.296*** (0.058)

Multinational firm –0.473*** (0.170)

–0.403*** (0.157)

–0.390*** (0.157)

–0.419*** (0.154)

Private firm –0.515*** (0.144)

–0.559*** (0.134)

–0.510*** (0.134)

–0.559*** (0.142)

Bulgaria –0.412* (0.242)

–0.368 (0.240)

–0.347 (0.234)

Hungary –0.267 (0.248)

–0.247 (0.247)

–0.198 (0.240)

Estonia –1.325*** (0.246)

–1.299*** (0.245)

–1.206*** (0.238)

Slovenia 0.974*** (0.225)

0.975*** (0.224)

1.005*** (0.219)

Slovakia –0.100 (0.218)

–0.077 (0.216)

–0.098 (0.210)

Business cycle -0.257*** (0.083)

-0.226*** (0.082)

Primary industries 0.969*** (0.174)

Manufacturing 0.577*** (0.133)

Construction 0.133 (0.242)

R_squared 0.27 0.34 0.51 0.52 0.58Number observations 680 680 680 680 680

Notes: Coefficients reported represent marginal effects. Reference country is Czech Republic, and reference industry is Services. Level of significance of estimated coefficients is 1%***, 5%**, 10%*.

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644 ILRREVIEW

density, negative movements in the business cycle, and institutional speci-ficities in certain countries. National patterns are broadly anticipated from nation-level studies, but the relationship between national and enterprise influence is not entirely symmetrical.

Our attempts to explain our findings originate in the continued and pos-itive importance of legacy union functions in the PSCs. Unions have certain positive resources: indirect union influence may derive, particularly among older workers, from conceptions of the union as welfare provider, and this may be more relevant than pre-1989 because job security is now hugely re-duced. It may also reflect continued identification with the union as an in-stitutional embodiment of the labor collective. Collaborative HRM reflects an approach that is more positive toward institutional forms of employee voice but its effects, which are weaker than in the United Kingdom, may also reflect the historic welfare orientation.

The country results confirm that our outliers in terms of national-level considerations, Slovenia and Estonia, show high and low enterprise-level union influence, respectively, and this reflects common estimates of their national influence. In the national middle range of our sample, union influ-ence in enterprises is similar in both parts of the ex-Czechoslovakia despite Slovakia’s relatively highly organized industrial relations (Stockhammer and Onaran 2009), and this suggests the relevance of these countries’ shared historic legacy.

Extrapolation from national-level estimates of union influence is not uni-versally valid. The marked weakness of Bulgarian enterprise-level union in-

Table 6b. Determinants of Union Presence in the United Kingdom (SUR estimator)

Variables

Models

(1) (2) (3) (4)

Firm size 0.319*** (0.046)

0.262*** (0.045)

0.265*** (0.045)

0.352*** (0.043)

Firm age 0.130*** (0.053)

0.135*** (0.052)

0.130** (0.052)

0.082* (0.049)

Multinational firm 0.210 (0.164)

0.189 (0.164)

0.086 (0.152)

Private firm –0.908*** (0.140)

–0.915*** (0.143)

–0.960*** (0.140)

Business cycle –0.072 (0.080)

–0.052 (0.075)

Primary industries 0.710** (0.298)

Manufacturing 1.426*** (0.132)

Construction 0.064 (0.310)

R_squared 0.25 0.34 0.34 0.47Number observations 800 800 800 800

Notes: Coefficients reported represent marginal effects. Reference industry is Services. Level of significance of estimated coefficients is 1%***, 5%**, 10%*.

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UNION INFLUENCE IN POST-SOCIALIST EUROPE 645

fluence is noteworthy. Although consistent with estimates from Global Union Federations’ local projects (ICEM/IUF 2009), this weakness is also surprising in view of Thirkell et al.’s (1998) earlier judgment and the mod-est level of transformation in that economy (Lane 2006).

We find a strong relationship between union influence and membership levels, and this finding supports Verma et al. (2002). Where union density is zero, the result is hardly surprising since no influence can be expected, but influence becomes more common with higher density. This may be inter-preted in different ways, and our no-influence finding may be more useful than the influence finding, because it is clearer in its meaning. This consti-tutes a limitation of our analysis because the latter undifferentiated category may conceal much variation. Conversely, a request for nuanced responses would introduce a major inter-rater reliability problem. Reaching a nuanced and context-sensitive assessment of union influence requires case study work.

Union influence is negatively correlated with the business cycle, espe-cially in the PSCs, and this is consistent with the thesis that union legal watchdog and welfare functions remain significant: Employer and worker demands for these services (especially the former) will likely be higher when enterprises are in difficulty, and this underlines the continuing significance of legal requirements that unions must be consulted on redundancies in some countries (Broughton 2009). The finding is consistent with Bulgarian findings that the onset of redundancy increases levels of union bargaining over its terms (Tomev et al. 2008). Private ownership of all types is also nega-tively associated with union influence. This suggests that private companies, including MNCs, are establishing employment relationships that tend to reduce union influence. It also implies that union influence in state enter-prises is unlikely to survive further privatization and foreign direct in vest-ment in these countries.

Overall, our findings lend little support to conceptions of convergence in Europe between East and West. Europe remains in this sense divided.

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Appendix

Table A.1a. HRM Practices Scales, PSCs

Scale/Variable

MSP

AlphaMean H

Calculative scale (CALC) 0.71 0.78Using compulsory redundancies 0.26 0.30 0.78Regular formal appraisal for manual workers 0.31 0.77 0.76Regular formal appraisal for clerical staff 0.40 0.71 0.76Regular formal appraisal for professionals 0.40 0.74 0.75Regular formal appraisal for managers 0.43 0.74 0.76Variable pay based on performance for manual workers 0.62 0.66 0.77Variable pay based on performance for clerical staff 0.65 0.74 0.76Base pay determined at individual level for clerical 0.68 0.81 0.77Base pay determined at individual level for professionals 0.69 0.80 0.77Base pay determined at individual level for manual workers 0.70 0.73 0.77Variable pay based on performance for professionals 0.70 0.74 0.76Formal appraisal used to inform career progress and pay 0.73 0.46 0.77Variable pay based on performance for managers 0.74 0.73 0.76In appraisal no input by the employee 0.78 0.30 0.78Base pay determined at individual level for managers 0.78 0.68 0.78Collaborative scale (COLL) 0.62 0.73Action programme for inclusion of minorities 0.30 0.30 0.73Formal briefings for manual workers 0.31 0.82 0.70Non-managerial career development by project team work 0.37 0.57 0.71Presence of joint consultative committee 0.44 0.30 0.73Formal briefings for clerical staff 0.46 0.72 0.70Managerial career development by project team work 0.50 0.49 0.70Procedure for employees to communicate to managers 0.54 0.48 0.71Strategy for communication to employees 0.59 0.58 0.71Formal briefings for professionals 0.64 0.69 0.69Employee-employer communication by team briefings 0.69 0.55 0.70Employer-employee communication by team briefings 0.72 0.58 0.70Written mission and corporate values statement 0.72 0.49 0.71Formal briefings for managers 0.92 0.70 0.72

Notes: MSP denotes Mokken Scaling Program. H is Loevinger’s coefficient of homogeneity (weighted); all H-coefficients are significantly different from zero at the p = 0.001 level. Alpha is Cronbach’s Alpha mea-= 0.001 level. Alpha is Cronbach’s Alpha mea- 0.001 level. Alpha is Cronbach’s Alpha mea-0.001 level. Alpha is Cronbach’s Alpha mea-sure of reliability for the scale; for each item, the Alpha is for the scale minus the item.

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UNION INFLUENCE IN POST-SOCIALIST EUROPE 647

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